freedom-mcp

report_feedback

Report an error, issue, observation, or suggestion you encountered during your work. Use this proactively when you notice something noteworthy — tool failures, recurring problems, quality issues, or improvement ideas. This helps the founder track and act on agent insights over time.

Routing: For issues YOU observe doing tenant work (tool failures, quality patterns) — lands in the operator's own observability feed. If the operator is reporting that FreedomOS ITSELF (platform UI/MCP/runtime) is broken or missing a capability, route to submit_product_request instead — FO product inbox only. Do NOT use submit_product_request for the tenant's own app/product/KB/retrieval gaps.

[write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema

Name	Required	Description
`title`	Yes	Short summary of the issue (1 line). Be specific — "Buffer API returns 429 on image posts" not "API error".
`category`	Yes	Type of feedback. error = something broke. warning = something might break. observation = pattern noticed. suggestion = improvement idea. blocker = cannot complete task.
`severity`	No	How urgent this is. Default: medium. Use critical only for data loss or security issues.
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.
`tool_name`	No	The tool that was involved, if applicable (e.g., "generate_image_xai", "post_to_x").
`description`	Yes	Detailed explanation. Include: what happened, what you expected, what you tried, and any error messages or codes.
`context_json`	No	Optional JSON-encoded structured context (error codes, retry counts, URLs, timestamps, etc.). Example: "{\"status\":429,\"retries\":3}".

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses routing behavior (tenant issues go to operator's feed, platform issues go elsewhere) and the approval process for write-tier. However, it does not mention what happens after submission (e.g., confirmation, feedback ID) or potential side effects, slightly reducing transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with two clear paragraphs and a bullet-like routing explanation. It is reasonably concise for the amount of information conveyed, though the approval note adds a bit of length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and 7 parameters, the description covers the tool's purpose, when to use, routing, and approval. It lacks details about the return value or confirmation, but the core context for decision-making is present. The mention of 'helps the founder track and act' is vague but sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond what the input schema provides—it focuses on tool purpose and usage rather than parameter details. The schema itself describes all parameters well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool's purpose: reporting errors, issues, observations, or suggestions. It uses specific verbs ('report') and resources ('error, issue, observation, or suggestion') and distinguishes from the sibling tool submit_product_request by specifying routing rules for platform vs. tenant issues.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool (proactively for noteworthy issues like tool failures, quality problems) and when not to (FreedomOS platform issues should go to submit_product_request). It also mentions the write-tier approval process, helping the agent understand constraints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0

Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources

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